Abstract: Methods and arrangements for filtering audio in a noisy environment involving receiving audio input at a user's location, using a plurality of audio input devices in proximity with a user. The audio is then separated into sources in response to a user selection. After the selection is made, the amplitudes of the audio sources are adjusted based on the selection. Other variants and embodiments are broadly contemplated herein.

Abstract: Generating a natural language dialog by finding missing semantic information in a user question by comparing it to the closest question available in a question corpus. Incrementally improved question precision is targeted during each round of the natural language dialog by generating follow-up questions that clarify semantic and syntactic characteristics of the user question. The follow-up questions are derived from analysis of the user question to identify areas of improvement on the user question.

Abstract: Generating a natural language dialog by finding missing semantic information in a user question by comparing it to the closest question available in a question corpus. Incremental improved question precision is targeted during each round of dialog.

Abstract: Methods and arrangements for filtering audio in a noisy environment involving receiving audio input at a user's location, using a plurality of audio input devices in proximity with a user. The audio is then separated into sources in response to a user selection. After the selection is made, the amplitudes of the audio sources are adjusted based on the selection. Other variants and embodiments are broadly contemplated herein.

Abstract: An illustrative mobile device includes a data storage configured to at least temporarily store visual information and at least one processor that is configured to determine whether to request visual information processing from a network with which the mobile device may communicate. The processor is configured to determine a mobile device condition and a network condition. The processor determines a type of feature from the visual information to use for classification based on the determined mobile device and network conditions. The processor is configured to classify the visual information based on the determined type of feature and determine a confidence indicator based on the classification. The processor determines whether to request visual information processing from the network based on the determined confidence indicator.

Abstract: An illustrative mobile device includes a data storage configured to at least temporarily store visual information and at least one processor that is configured to determine whether to request visual information processing from a network with which the mobile device may communicate. The processor is configured to determine a mobile device condition and a network condition. The processor determines a type of feature from the visual information to use for classification based on the determined mobile device and network conditions. The processor is configured to classify the visual information based on the determined type of feature and determine a confidence indicator based on the classification. The processor determines whether to request visual information processing from the network based on the determined confidence indicator.